Journal of Signal and Information Processing, 2015, 6, 123-135 Published Online May 2015 in SciRes. http://www.scirp.org/journal/jsip http://dx.doi.org/10.4236/jsip.2015.62012 How to cite this paper: Abo-Zahhad, M., Gharieb, R.R., Ahmed, S.M. and Abd-Ellah, M.K. (2015) Huffman Image Compres- sion Incorporating DPCM and DWT. Journal of Signal and Information Processing, 6, 123-135. http://dx.doi.org/10.4236/jsip.2015.62012 Huffman Image Compression Incorporating DPCM and DWT Mohamed Abo-Zahhad 1 , Reda Ragab Gharieb 1 , Sabah M. Ahmed 1 , Mahmoud Khaled Abd-Ellah 2 1 Department of Electrical and Electronics Engineering, Faculty of Engineering, Assiut University, Assiut, Egypt 2 Department of Electronics and Communication Engineering, Madina Higher Institute for Engineering and Technology, Giza, Egypt Email: Eng_mahmoudkhaled@yahoo.com Received 5 March 2015; accepted 22 April 2015; published 24 April 2015 Copyright © 2015 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract This paper presents a medical image compression approach. In this approach, first the image is pre-processed by Differential Pulse Code Modulator (DPCM), second, the output of the DPCM is wavelet transformed, and finally the Huffman encoding is applied to the resulting coefficients. Therefore, this approach provides theoretically threefold compression. Simulation results are pre- sented to compare the performance of the proposed (DPCM-DWT-Huffman) approach with the per- formances of the Huffman incorporating DPCM (DPCM-Huffman), the DWT-Huffman and the Huff- man encoding alone. Several quantitative indexes are computed to measure the performance of the four algorisms. The results show that the DPCM-DWT-Huffman, the DWT-Huffman, the DPCM- Huffman and the Huffman algorisms provide compression ratio (CR) of 6.4837, 4.32, 2.2751 and 1.235, respectively. The results also confirm that while the proposed DPCM-DWT-Huffman approach enhances the CR, it does not deteriorate other performance quantitative measures in compari- son with the DWT-Huffman, the DPCM-Huffman and the Huffman algorisms. Keywords Medical Image Compression, Brain Image Compression, CT, DPCM, DWT, CR 1. Introduction The main objective of image compression techniques is to reduce the image size for less storage and transmis- sion bandwidth by discarding irrelevance and redundancy of the image data. These techniques can be classified into two categories: lossless and lossy compression techniques. Lossless techniques are applied when data are